• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.2
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• pp.45-51
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• 2003

The multi-piloting type progressive die for U-bending sheet metal production part is a very specific division. This study reveals the sheet metal forming process with multi-forming die by center carrier type feeding system. Through the FEM simulation by DEFORM, it was accepted to u-bending process as the first performance to design of strip process layout. The next process of die development was studied according to sequence of die development, i.e die structure, machining condition for die making, die materials, heat treatment of partially die components, know-how and so on. The feature of this study is the die development of scrapless progressive die of multi-stage through the modeling on the I-DEAS program, components drawing on the Auto-LISP, CAD/CAM application, ordinary machine tool operating and revision by tryout.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.87-92
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• 1999

The biggest challenge facing today manufacturing industry is better quality and high productivity. From an economic point of view, productivity is the most important parameter, as high productivity will reduce the cost. However, the customers of today are not only cost concerned, but also quality conscious. So high accuracy levels should also be achieved in the manufacturing process. This paper reports the development of a automatic design system based on AutoCAD program. This work is composed of three section that are design of top down menu, guide frame and gate lifter for water-gate programed by AutoLISP language and runned Windows system. The developed system ultimately generates the design for a water gate through AutoCAD program. In the design of the water gate, it needs about 23 hours with an expert, but this system can be only 80 seconds without an expert.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.209-216
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• 1997

A feature is well known as a medium to integrate CAD, CAPP and CAM systems. For a part drawing including both simple geometry and compound geometry, a process plan such as the selection of process, machine tool, cutting tool etc. normally needs simple geometry data and non-geometry data of the feature as the input. However, a extended process plan such as the generation of process sequence, operation sequence, jig & fixture, NC program etc. necessarily needs the compound geometry data as well as the simple geometry data and non-geometry data. In this paper, we propose a feature data model according to the result of analyzing necessary data, including the compound geometry data, the simple geometry data and the non-geometry data. Also, an example of the feature data model in milling process planning is described.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.249-254
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• 2000

The contact forces between die components for the drawing of large size automotive panels introduce elastic deflections of the die components. Due to the deflections, the gap between blank holder and die varies locally resulting in nonuniform material flow. Such a nonuniform die gap usually requires correcting operation, so called die spotting, which is time consuming trial and error process. To reduce the die spotting time, the optimization of the blank holder bending deflection is needed. In this paper, we implemented an analysis procedure to predict the blank holder deflection. The analysis procedure and design of experiments techniques are applied to the optimization of balance block heights. The optimization results can be used as guidelines in actual die spotting process.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.398-401
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• 2005

The characteristic of sheet metal process is the few loss of material during process, the short processing time and the excellent price and strength. Such press-forming process are the used machine ability and the characteristic, used material, the accuracy of the part which becomes processing and side condition of a process are considered and the designed. The purpose of this study is apply efficiently sheet metal forming processing by 3D formation-analyzed program simulations in the site. By a study, forming process was simulation to drawing and trimming and cam process using static-implicit method software. By making apply this to an industrial site the productivity improvement and cost reduction etc. effect able was predicted.

• Transactions of Materials Processing
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• v.8 no.5
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• pp.465-470
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• 1999

Many researchers have, nowadays, studied on spinning which can produce highly qualified products by CNC spinning machine equipped with hydraulic devices. The products have continuous metal flow which improves fatigue life, yield point, tensile strength and hardness. This study is to investigate the influence of various working conditions on the spinnability of cylindrical cups such as feed rate(ν), feed pitch(p), angle of roller holder(α), and the inclination angle of first roller path. Through experiments the feed rate of (0.4∼0.7) mm/rev was shown to give the drawing ratio of 2.5 when the angle of roller holder was 5°, However, by increasing the angle of roller holder from 5°to 20°, the range of feed rate which can produce deeper cups became wider and the spinnability was also improved. The optimum working conditions, for the maximum formability of aluminum sheet metal as well as dimensional accuracy of spun cups, are presented and discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.2
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• pp.89-93
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• 2002

PbO contained multicomponent glass and fibers have been obtained by melting process and double crucible method. PbO containing glass is most promising for fabrication of high-numerical aperture optical fiber. In this study, main composition is $SiO_2$, PbO and glass composition mix component oxide such as $K_2O$, $Na_2O$, $B_2O_3$, $A1_2O_3$. Also, the optical, mechanical and structural properties of manufactured fibers by double crucible method are investigated.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.269-277
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• 1986

This paper proposes a new algorithmic state machine(ASM) chart and a new hardware description for automatic logic design of VLSI. To describe the behavioral characteristics of the design specification, the conventional ASM chart is modified, and a new hardware description language, SDL, is proposed. The SDL is one-to-one correspondent to the proposed ASM chart symbol, and can be used in a hierachical design of VLSI. As a design example, we obtain a logic circuit diagram of gate lebel utilizing a SDL hardware compiler after drawing an ASM chart and describing in SDL.

• Macromolecular Research
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• v.17 no.6
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• pp.378-387
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• 2009

This research compared three methods for producing and processing nanocomposite polypropylene filament yarns with permanent antimicrobial efficiency. The three methods used to mix antimicrobial agents based on silver nano particles with PP were as follows: 1) mixing of PP powder and inorganic nanocomposite filler with the appropriate concentration using a twin-screw extruder and preparing granules, 2) method 1 with a singlerather than twin-screw extruder, and 3) producing the masterbatch by a twin-screw extruder and blending it with PP in the melt spinning process. All pure polypropylene samples and other combined samples had an acceptable spinnability at the spinning temperature of $240^{\circ}C$ and take-up speed of 2,000 m/min. After producing as-spun filament yarns by a pilot plant, melt spinning machine, the samples were drawn, textured and finally weft knitted. The physical and structural properties (e.g., linear density, tenacity, breaking elongation, initial modulus, rupture work, shrinkage and crystallinity) of the as-spun and drawn yarns with constant and variable draw ratios (the variable draw ratio was used to gain a constant breaking elongation of 50%) were investigated and compared, while DSC, SEM and FTIR techniques were used to characterize the samples. Finally, the antibacterial efficiency of the knitted samples was evaluated. The experimental results revealed that the crystallinity reduction of the as-spun yarn obtained from method 1 (5%) was more than that of method 2 (3%), while the crystallinity of the modified as-spun yarns obtained with method 3 remained unchanged compared to pure yarn. However, the drawing procedure compensated for this difference. By applying methods 2 and 3, the drawing generally improved the tenacity and modulus of the modified fibers, whereas method 1 degraded the constant draw ratio. Although the biostatic efficiency of the nanocomposite yarns was excellent with all three methods, the modified fabrics obtained from methods 1 and 2 showed a higher bioactivity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.206-216
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• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.